Ultimate Agentic AI with AutoGen for Enterprise Automation
eBook - ePub

Ultimate Agentic AI with AutoGen for Enterprise Automation

Design, Build, And Deploy Enterprise-Grade AI Agents Using LLMs and AutoGen To Power Intelligent, Scalable Enterprise Automation (English Edition)

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Ultimate Agentic AI with AutoGen for Enterprise Automation

Design, Build, And Deploy Enterprise-Grade AI Agents Using LLMs and AutoGen To Power Intelligent, Scalable Enterprise Automation (English Edition)

About this book

Empowering Enterprises with Scalable, Intelligent AI Agents.Key Features? Hands-on practical guidance with step-by-step tutorials and real-world examples.? Build and deploy enterprise-grade LLM agents using the AutoGen framework.? Optimize, scale, secure, and maintain AI agents in real-world business settings.Book DescriptionIn an era where artificial intelligence is transforming enterprises, Large Language Models (LLMs) are unlocking new frontiers in automation, augmentation, and intelligent decision-making.Ultimate Agentic AI with AutoGen for Enterprise Automation bridges the gap between foundational AI concepts and hands-on implementation, empowering professionals to build scalable and intelligent enterprise agents.The book begins with the core principles of LLM agents and gradually moves into advanced topics such as agent architecture, tool integration, memory systems, and context awareness. Readers will learn how to design task-specific agents, apply ethical and security guardrails, and operationalize them using the powerful AutoGen framework. Each chapter includes practical examples—from customer support to internal process automation—ensuring concepts are actionable in real-world settings.By the end of this book, you will have a comprehensive understanding of how to design, develop, deploy, and maintain LLM-powered agents tailored for enterprise needs. Whether you're a developer, data scientist, or enterprise architect, this guide offers a structured path to transform intelligent agent concepts into production-ready solutions.What you will learn? Design and implement intelligent LLM agents using the AutoGen framework.? Integrate external tools and APIs to enhance agent functionality.? Fine-tune agent behavior for enterprise-specific use cases and goals.? Deploy secure, scalable AI agents in real-world production environments.Table of Contents1. Introduction to LLM Agents (Foundation and Impact)2. Architecting LLM Agents (Patterns and Frameworks)3. Building a Task-Oriented Agent using AutoGen4. Integrating Tools for Enhanced Functionality5. Context Awareness and Memory System6. Designing Multi-Agent Systems7. Evaluation Framework for Agents and Tools8. Agent-Security, Guardrails, Trust, and Privacy9. LLM Agents in Production10. Use Cases for Enterprise LLM Agents11. Advanced Prompt Engineering for Effective AgentsIndexAbout the AuthorsShekhar Agrawal, Senior Director of Data Science at Oracle, is an AI and data engineering expert with over 14 years of experience. He leads the development of Generative AI platforms and enterprise-scale machine learning systems that support thousands of customers worldwide.Srinivasa Sunil Chippada is a skilled Data Science Engineering expert with 19 years of experience in building scalable enterprise data systems. He offers valuable technical insights for maximizing data value through Feature Stores, Data Marts, Data pipelines and Data Integration techniques.Rathish Mohan is a distinguished applied scienti

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Yes, you can access Ultimate Agentic AI with AutoGen for Enterprise Automation by Shekhar Agrawal,Srinivasa Sunil Chippada,Rathish Mohan in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Title Page
  3. Copyright Page
  4. Dedication Page
  5. About the Authors
  6. About the Technical Reviewer
  7. Acknowledgements
  8. Preface
  9. Get a Free eBook
  10. Errata
  11. Table of Contents
  12. 1. Introduction to LLM Agents (Foundation and Impact)
  13. 2. Architecting LLM Agents (Patterns and Frameworks)
  14. 3. Building a Task-Oriented Agent Using AutoGen
  15. 4. Integrating Tools for Enhanced Functionality
  16. 5. Context Awareness and Memory System
  17. 6. Designing Multi-Agent Systems
  18. 7. Evaluation Framework for Agents and Tools
  19. 8. Agent-Security, Guardrails, Trust, and Privacy
  20. 9. LLM Agents in Production
  21. 10. Use Cases for Enterprise LLM Agents
  22. 11. Advanced Prompt Engineering for Effective Agents
  23. Index